System Theory, Computational Social Science and the Challenges of Zettabyte Era

The volume of information available for research has grown rapidly in recent decades. According to the Cisco Systems, we are beginning the era of Zettabyte. The access and analytical treatment of this enormous amount of information have created a debate in social sciences about new methods, epistemological and theoretical conceptions. This study is based on systems theory, sociocybernetics and new propositions of the computational social science. Four concepts connect the areas of knowledge involved in this project: system, complexity, emergence and evolution. The fundamental premise to make sense of the data is that a social organization evolves or transform over time. Data can be conceived as a registry of how systems are organized and how it changes over time. In the classical sociology, the same idea constitutes the fundamental concept of the social process, which can be identified through social patterns. It means that social phenomena emerge from social relations, even if individuals are rational agents of these changes. The methodological challenge consists in observing and selecting data to reveal patterns of social relations and unravel the interconnection between the components of a system. The intention is to understand emergence of social phenomena (migration, inequality, etc.) and the consequent change in the social system. This study, conduct by the Laboratory of computational sociology (Infosoc - UEL), has approached agent-based simulations in comparison with observed data from social networks. The first conclusions are the volume of data is less significant than the analytical capacity to select specific data in order to identify social interconnections and find patterns of systems complexity.